scholarly journals Cloud Computing in Bioinformatics: current solutions and challenges

2016 ◽  
Author(s):  
Barbara Calabrese ◽  
Mario Cannataro
Keyword(s):  
Experimental Data ◽  
Cloud Computing ◽  
Data Storage ◽  
High Throughput ◽  
Virtual Space ◽  
Security And Privacy ◽  
Analysis Pipeline ◽  
Complete Control ◽  
Platform As A Service ◽  
Wide Range

Abstract truncated at 3,000 characters - the full version is available in the pdf file MOTIVATIONS The availability of high-throughput technologies and the application of genomics and pharmacogenomics studies of large populations, are producing an increasing amount of experimental and clinical data, as well as specialized databases spread over the Internet. The storage, preprocessing and analysis of experimental data is becoming the main bottleneck of the analysis pipeline. Managing omics data requires both space for data storing as well as services for data preprocessing, analysis, and sharing. The resulting scenario comprises a set of bioinformatics tools, often implemented as web services, for the management and analysis of data stored in geographically distributed biological databases [1]. Cloud computing may play an important role in many phases of the bioinformatics analysis pipeline, from data management and processing, to data integration and analysis, including data exploration and visualization because it offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, thus it may represent the key technology for facing those issues [2]. METHODS This work reviews main academic and industrial cloud-based bioinformatics solutions developed in the recent years; moreover, it underlines main issues and problems related to the use of such platforms for the storage and analysis of patients’ data. Specifically, the analysed solutions regard: - Data as a Service (DaaS): it provides data storage in a dynamic virtual space hosted by the cloud and allows to have updated data that are accessible from a wide range of connected devices on the web. - Software as a Service (SaaS): several cloud-based tools to execute different bioinformatics tasks, e.g. mapping applications, sequences alignment, gene expression analysis have been proposed and made available. - Platform as a Service (PaaS): unlike SaaS solutions, PaaS solutions allow users to customize the deployment of bioinformatics applications as well as to retain complete control over their instances and associated data. - Infrastructure as a Service (IaaS): this service model is offered in a computing infrastructure that includes servers (typically virtualized) with specific computational capability and/or storage. The user controls all the deployed storage resources, operating systems and bioinformatics applications. For each analysed solution, main technical characteristics as well as security and privacy issues arising when storing and analysing patients data, are reported. RESULTS The application of cloud computing in bioinformatics regards the efficient storage, retrieval and integration of experimental data and their efficient and high-throughput preprocessing and analysis.

scholarly journals Cloud Computing in Bioinformatics: current solutions and challenges

2016 ◽  
Author(s):  
Barbara Calabrese ◽  
Mario Cannataro
Keyword(s):  
Experimental Data ◽  
Cloud Computing ◽  
Data Storage ◽  
High Throughput ◽  
Virtual Space ◽  
Security And Privacy ◽  
Analysis Pipeline ◽  
Complete Control ◽  
Platform As A Service ◽  
Wide Range

Abstract truncated at 3,000 characters - the full version is available in the pdf file MOTIVATIONS The availability of high-throughput technologies and the application of genomics and pharmacogenomics studies of large populations, are producing an increasing amount of experimental and clinical data, as well as specialized databases spread over the Internet. The storage, preprocessing and analysis of experimental data is becoming the main bottleneck of the analysis pipeline. Managing omics data requires both space for data storing as well as services for data preprocessing, analysis, and sharing. The resulting scenario comprises a set of bioinformatics tools, often implemented as web services, for the management and analysis of data stored in geographically distributed biological databases [1]. Cloud computing may play an important role in many phases of the bioinformatics analysis pipeline, from data management and processing, to data integration and analysis, including data exploration and visualization because it offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, thus it may represent the key technology for facing those issues [2]. METHODS This work reviews main academic and industrial cloud-based bioinformatics solutions developed in the recent years; moreover, it underlines main issues and problems related to the use of such platforms for the storage and analysis of patients’ data. Specifically, the analysed solutions regard: - Data as a Service (DaaS): it provides data storage in a dynamic virtual space hosted by the cloud and allows to have updated data that are accessible from a wide range of connected devices on the web. - Software as a Service (SaaS): several cloud-based tools to execute different bioinformatics tasks, e.g. mapping applications, sequences alignment, gene expression analysis have been proposed and made available. - Platform as a Service (PaaS): unlike SaaS solutions, PaaS solutions allow users to customize the deployment of bioinformatics applications as well as to retain complete control over their instances and associated data. - Infrastructure as a Service (IaaS): this service model is offered in a computing infrastructure that includes servers (typically virtualized) with specific computational capability and/or storage. The user controls all the deployed storage resources, operating systems and bioinformatics applications. For each analysed solution, main technical characteristics as well as security and privacy issues arising when storing and analysing patients data, are reported. RESULTS The application of cloud computing in bioinformatics regards the efficient storage, retrieval and integration of experimental data and their efficient and high-throughput preprocessing and analysis.

scholarly journals Privacy and Security in Cloud Computing Architecture

2020 ◽  
pp. 174-179
Author(s):  
Yin Myo Kay Khine Thaw ◽  
Myo Ma Ma ◽  
Khin Myat New Win
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Computing Architecture ◽  
Cloud Computing Adoption ◽  
Wide Range ◽  
Computing Platforms ◽  
High Level ◽  
Cloud Interoperability

Cloud Computing is the most advanced technical platform for next generation. Cloud Computing provide us a large range of data storage space in web source. Cloud Computing work automatically as per the need of user we don’t need to do extra work on it. High level applications and game is run by Cloud Computing. It simply states that cloud computing means storing and accessing the data and programs over the internet rather than the computer’s hard disk. Cloud Computing cover the wide range of areas. It provides its service through online net connection. The data can be anything such as music, files, images, documents, and more. The user can access the data from anywhere just with the help of an internet connection. To use cloud computing, the user should register and provide with ID and password for security reasons. The speed of transfer depends on various factors such as the capacity of the server, internet speed, and many more. In this paper, we explore the understanding the determinates of security and privacy in cloud computing, Cloud Computing architecture and we also address the characteristics and applications of several popular cloud computing platforms. We identified several challenges from the cloud computing adoption perspective and we also highlighted the cloud interoperability issue that deserves substantial further research and development. However, security and privacy issues present a strong barrier for users to adapt into cloud computing systems.

scholarly journals LAYANAN CLOUD COMPUTING BERBASIS INFRASTRUCTURE AS A SERVICE MENGGUNAKAN ANDROID

Compiler ◽  
2015 ◽  
Vol 4 (2) ◽  
Author(s):  
Hero Wintolo ◽  
Lalu Septian Dwi Paradita
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Wireless Lan ◽  
Information Technologies ◽  
Computer Software ◽  
Computer Hardware ◽  
Local Network ◽  
Infrastructure As A Service ◽  
Platform As A Service ◽  
Service Application

Cloud computing, one form of information technologies are widely used in the field of computer networks or the Internet. Cloud computing consists of computer hardware, computer networking devices, and computer software, the cloud computing there are three services provided include (SaaS) Software as a Service (PaaS) Platform as a Service, and (IaaS) Infrastructure as a Service. Application cloud computing services in the wake of this system is a service-based data storage infrastructure as a service by using android smartphone as a storage medium, which utilizes FTP Server which is already available on the smartphone. This certainly supports the easy storage of data that utilize various types of internal and external storage on smartphones that serves as a storage server. In addition to the functions of storage available, this service can accommodate streaming function .mp3 file type. Implementation result of the system can be implemented on a local network using a wireless LAN. In addition, the results of user testing using Likert method shows the application can run and function properly

scholarly journals A New Secure Model for Data Protection over Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Amr M. Sauber ◽  
Passent M. El-Kafrawy ◽  
Amr F. Shawish ◽  
Mohamed A. Amin ◽  
Ismail M. Hagag
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Protection ◽  
Cloud Services ◽  
Security And Privacy ◽  
Storage Model ◽  
Cloud Data ◽  
Security Issues ◽  
Data Owner ◽  
Proposed Model

The main goal of any data storage model on the cloud is accessing data in an easy way without risking its security. A security consideration is a major aspect in any cloud data storage model to provide safety and efficiency. In this paper, we propose a secure data protection model over the cloud. The proposed model presents a solution to some security issues of cloud such as data protection from any violations and protection from a fake authorized identity user, which adversely affects the security of the cloud. This paper includes multiple issues and challenges with cloud computing that impairs security and privacy of data. It presents the threats and attacks that affect data residing in the cloud. Our proposed model provides the benefits and effectiveness of security in cloud computing such as enhancement of the encryption of data in the cloud. It provides security and scalability of data sharing for users on the cloud computing. Our model achieves the security functions over cloud computing such as identification and authentication, authorization, and encryption. Also, this model protects the system from any fake data owner who enters malicious information that may destroy the main goal of cloud services. We develop the one-time password (OTP) as a logging technique and uploading technique to protect users and data owners from any fake unauthorized access to the cloud. We implement our model using a simulation of the model called Next Generation Secure Cloud Server (NG-Cloud). These results increase the security protection techniques for end user and data owner from fake user and fake data owner in the cloud.

scholarly journals Improvement of Privacy and Security in Hybrid Cloud with Attribute Group Based Access Control

2019 ◽  
pp. 57-61
Author(s):  
Kayalvili S ◽  
Sowmitha V
Keyword(s):  
Cloud Computing ◽  
Access Control ◽  
Data Storage ◽  
Service Providers ◽  
Cloud Service ◽  
Security Requirements ◽  
Security And Privacy ◽  
Data Outsourcing ◽  
Privacy And Security ◽  
Control Approach

Cloud computing enables users to accumulate their sensitive data into cloud service providers to achieve scalable services on-demand. Outstanding security requirements arising from this means of data storage and management include data security and privacy. Attribute-based Encryption (ABE) is an efficient encryption system with fine-grained access control for encrypting out-sourced data in cloud computing. Since data outsourcing systems require flexible access control approach Problems arises when sharing confidential corporate data in cloud computing. User-Identity needs to be managed globally and access policies can be defined by several authorities. Data is dual encrypted for more security and to maintain De-Centralization in Multi-Authority environment.

Confidentiality and Safekeeping Problems and Techniques in Fog Computing

2021 ◽  
pp. 1855-1873
Author(s):  
Nida Kauser Khanum ◽  
Pankaj Lathar ◽  
G. M. Siddesh
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Fog Computing ◽  
Video Stream ◽  
Security And Privacy ◽  
Surveillance Video ◽  
Speech Data ◽  
Real Time Applications ◽  
Privacy Issues ◽  
Intrusion Detection And Prevention

Fog computing is an extension of cloud computing, and it is one of the most important architypes in the current world. Fog computing is like cloud computing as it provides data storage, computation, processing, and application services to end-users. In this chapter, the authors discuss the security and privacy issues concerned with fog computing. The issues present in cloud are also inherited by fog computing, but the same methods available for cloud computing are not applicable to fog computing due to its decentralized nature. The authors also discuss a few real-time applications like healthcare systems, intelligent food traceability, surveillance video stream processing, collection, and pre-processing of speech data. Finally, the concept of decoy technique and intrusion detection and prevention technique is covered.

Study and Survey on Blockchain Privacy and Security Issues

2021 ◽  
pp. 169-191
Author(s):  
Sourav Banerjee ◽  
Debashis Das ◽  
Manju Biswas ◽  
Utpal Biswas
Keyword(s):  
Data Storage ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Privacy And Security ◽  
Unauthorized Access ◽  
Security Issues ◽  
Blockchain Technology ◽  
Targeted Attacks ◽  
Wide Range ◽  
Financial Transactions

Blockchain-based technology is becoming increasingly popular and is now used to solve a wide range of tasks. And it's not all about cryptocurrencies. Even though it's based on secure technology, a blockchain needs protection as well. The risks of exploits, targeted attacks, or unauthorized access can be mitigated by the instant incident response and system recovery. Blockchain technology relies on a ledger to keep track of all financial transactions. Ordinarily, this kind of master ledger would be a glaring point of vulnerability. Another tenet of security is the chain itself. Configuration flaws, as well as insecure data storage and transfers, may cause leaks of sensitive information. This is even more dangerous when there are centralized components within the platform. In this chapter, the authors will demonstrate where the disadvantages of security and privacy in blockchain are currently and discuss how blockchain technology can improve these disadvantages and outlines the requirements for future solution.

scholarly journals Research on Security Architecture in Mobile Cloud Computing to Prevent Adaptive Anomaly Attacks

2019 ◽  
Vol 8 (6S4) ◽  
pp. 942-947
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Security ◽  
Data Privacy ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Data Accessibility ◽  
Security Issues ◽  
Wide Range ◽  
Rapid Pace

Cloud Computing is a very viable data storage structure where the users can store and access the data from anywhere. Cloud computing use is increasing at a very rapid pace nowadays. But as cloud allows us data accessibility quite easily data security is a major concern and is an emerging area of study. Other issues related to cloud computing are data privacy and internet dependency. On the other cloud computing also has wide range of benefits over traditional storage and accessibility environment such as scalability, flexibility and resource utilization. We have worked in the area of mobile cloud computing to analyse and solve the problems of anomaly attacks. Our work focuses on preventing the adaptive anomaly attacks and some other security issues of cloud computing

scholarly journals «Digital Lab» Platform as an Environment for Scientific Research and Development at the Kurchatov Institute

2020 ◽  
Vol 32 (5) ◽  
pp. 143-152
Author(s):  
Andrey N. Polyakov ◽  
Irina M. Enyagina ◽  
Dmitry S. Kokovin
Keyword(s):  
Experimental Data ◽  
Research And Development ◽  
Data Exchange ◽  
Virtual Machines ◽  
Scientific Research ◽  
Virtual Space ◽  
Wide Range ◽  
Computing Center ◽  
Processing And Storage ◽  
And Storage

The Kurchatov Complex of NBICS Nature-Like Technologies is focused on interdisciplinary research and development in the field of nano-, bio-, information, cognitive, socio-humanitarian sciences and technologies. The experimental basis of the NBICS complex is the Resource Centers operating in the mode of collective use by various scientific laboratories and containing modern equipment for conducting a wide range of scientific experiments. The processing and storage of the obtained experimental data is carried out on the supercomputer of the Computing Center, the use of which is also collective. Thus, there are problems of data exchange between different buildings, organizing their processing, analysis and orderly storage, as well as combining heterogeneous experimental data to obtain scientific results of a higher level. To solve these issues on the basis of the distributed modular platform «Digital Laboratory», an information and analytical environment was organized as a system that combines the scientific equipment of the Resource Centers, the supercomputer of the Computing Center, virtual machines and personal computers of scientific laboratories into a single virtual space, while organizing the exchange of data between various buildings, their processing, analysis and storage. The work with the system is carried out through the user web interface. At the request of researchers, each procedure for working with experimental data of a given type is implemented as an autonomous module of the «Digital Laboratory» platform. For example, the Module «Neuroimaging» for processing and analysis of fMRI / MRI experimental data of the human brain obtained on the tomograph of the Resource Center was put into operation and is successfully functioning. The use of this module makes the task of fMRI / MRI data analysis as simple as possible for the user, and also makes it possible to speed up the data processing many times over by parallelizing the computations on the supercomputer nodes. In addition to creating modules for working with experimental data, the system provides the ability to create modules for working with data of a different type. An example is the Module «Project Activity» for analyzing the effectiveness of scientific activities of research laboratories. The use of this system allows to optimize the work with experimental data in the course of scientific research due to the possibility of software implementation of the necessary procedures for their transfer, storage, processing and analysis.

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